Generally, machine learning may be understood as a method of data analysis that learns a model from historical data, which can then be applied to extract implicit knowledge from future data. In the context of opportunity based cognitive decision-making process and system, machine-learning method by itself alone is inadequate because of continuous man-machine interactions and dynamic changes in the decision-making environment. Furthermore, the conventional machine learning systems and methods lack the ability to reflect upon the contextual decision-making process and to take into account numerous model interdependencies that may degrade the performance of learned models in an unpredictable manner.